Cloud, Data, AI/ML, Serverless and Open Source

In
2018, the enterprise tech world saw a lot of momentum in cloud, data,
serverless, AI and machine learning. From strong pivots to cloud strategies,
GDPR taking effect, new infrastructures rising in popularity and machine
learning picking up steam, 2018 laid the groundwork for these trends to really
take off next year. Here is what we at Talend predict are going to be the main
showstoppers in 2019.

Cloud

The business
multi-verse expands through multi-cloud as data inefficiencies are solved:
Multi-cloud
promises tremendous reward if it can be used properly, but data
inefficiencies and complicated compliance policies hinder progress for
many. 2019 will see some of those data inefficiencies fade away as
effective data strategies are implemented and new technologies unleash
true multi-cloud functionality to the masses.

AI / Machine Learning / ML
Trust/ethics/bias

Questions around
data morality will slow innovation in AI/ML: The past year has
seen the hype around AI/ML explode, and data ethics, trust, bias and
fairness have all surfaced to combat inequalities in the process to make
everything intelligent. There are many layers to data morality, and while
ML advancements won't cease -- they'll slow down in 2019 as researchers
try to hash out a fair, balanced approach to machine-made decisions.

The black box of
algorithms becomes less opaque: Part of the issue with data morality with
AI and machine learning is that numbers and scenarios are crunched without
insight into subsequent answers came to be. Even researchers can have a
hard time sorting it out after the fact. But in the coming years, while it
won't lead to complete transparency with proprietary algorithms, the black
box will still become less opaque as end users become increasingly
educated about data and how it's used.

GDPR / CA Consumer Privacy Laws /
Data Privacy

The "G" in GDPR
Will Soon Stand for "Global": Data privacy regulations are going to
become more widespread. For example, California, Japan and China are
already working on their own regulations to adopt rules similar to the
EU's GDPR. Additionally, companies like Facebook, Google and Twitter have
all severely mishandled consumer data, showing the need for increased and
widespread data privacy regulations -- even prompting Apple CEO Tim Cook
to call for global privacy regulations. With consumers now viewing data
privacy as a human right, increased data governance policies are sure to
follow.

As privacy
regulations spread, organizations will mistake data governance for data
harassment:
Based on what consumers do online, companies are able to determine,
through their data, their demographics, interests and even what's going on
in their personal lives. This results in marketing so hyper targeted, it
could feel like harassment. While organizations struggle to comply with
privacy regulations and create more well rounded and informed views of
each of their consumers, the lines between governance and harassment will
blurr, and there will be rocky roads as best practices are formed.

Social media is
officially too big to fail: Social media companies have become the
biggest publishing media brands and they finally came under scrutiny this
year. However, there were no real repercussions for advertising fiascos
and data privacy controversies despite Congress's involvement, and the
reality is that social media brands have become too big to fail. While
there will still be fights to remedy it -- and there should be work done
on this end -- 2019 will solidify how social media companies are now too
big to fail (or become regulated).

Data Skills / Data as a team sport

The data skills
gap will increase - but so will data literacy: Data is both the
problem and the answer for businesses. It's a problem because businesses
manage to collect more data than they know how to use, yet it's the answer
because it can predict forecasts and offer insight into how the business
should run. The next year will see the data skills gap continue to
increase -- users need to be able to analyze properly where data comes
from and how to use it, and it only gets more complicated as more data is
made available and as algorithms enter the fray. But at the same time,
business users will also grow more data literate as they seek to approach
data as a team, and help one another get what they need from their data.

Serverless and Open Source

Serverless will
move beyond the hype as developers take hold: 2018 was all
about understanding what serverless is, but as more developers learn the
benefits and begin testing in serverless environments, more tools will be
created to allow them to take full advantage of the architecture and to
leverage functions-as-a-service. Serverless will create new application
ecosystems where startups can thrive off the low-cost architecture and
creatively solve deployment challenges.

The market will double down
on open source technologies: 2018 has seen $53 billion in deals involving open
source following the Cloudera/Hortonworks merger and acquisitions of Red Hat,
GitHub and others. 2019 will see businesses double down on open source
technologies -- more investments and deals will get done, and open source
communities will also pour more effort and energy into projects after having
seen the opportunity for open source in the marketplace. To-date, open source
has still functioned with a freemium model, but the coming years may see that
shift as the enterprise finds value in conventional open source technologies.

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About the Author

Laurent
Bride joined Talend in 2014 as chief technical officer. He came with 17 years
of software experience during which he held various individual, management and
executive roles in customer support and product development. Laurent holds an
engineering degree in mathematics and computer science from EISTI.